class_docstr: Grappler Clusters.
class_docstr_tok: ["Grappler","Clusters","."]
docstr: Returns the cost of running the specified item.
  
  Args:
    item: The item for which to measure the costs.
  Returns: The triplet op_perfs, runtime, step_stats.
docstr_tok: ["Returns","the","cost","of","running","the","specified","item",".","Args",":","item",":","The","item","for","which","to","measure","the","costs",".","Returns",":","The","triplet","op_perfs",",","runtime",",","step_stats","."]
code: def MeasureCosts(self, item):
      """Returns the cost of running the specified item.
  
      Args:
        item: The item for which to measure the costs.
      Returns: The triplet op_perfs, runtime, step_stats.
      """
      (
          op_perf_bytes_list,
          run_time,
          step_stats_bytes,
      ) = tf_cluster.TF_MeasureCosts(
          item.tf_item, self._tf_cluster, self._generate_timeline
      )
  
      op_perfs = [
          op_performance_data_pb2.OpPerformance.FromString(
              op_perf_bytes
          )
          for op_perf_bytes in op_perf_bytes_list
      ]
      return (
          op_perfs,
          run_time,
          step_stats_pb2.StepStats.FromString(step_stats_bytes),
      )
  
file_path: tensorflow-upstream/tensorflow/python/grappler/cluster.py
imports: import contextlib
  from tensorflow.core.framework import step_stats_pb2
  from tensorflow.core.grappler.costs import op_performance_data_pb2
  from tensorflow.core.protobuf import device_properties_pb2
  from tensorflow.python.grappler import _pywrap_tf_cluster
label_desc: Use image node_id 9 for calling the Cluster obj's underlying member method code with example usage: obj.MeasureCosts(item) and returns: op_perfs,  run_time,  step_stats_pb2